Working in 32-bit and 64-bit systems, FaceSDK is used to build Web, Windows, Linux, Mac OS X, iOS and Android applications, and enables face-based biometric authentication on still images and real-time video streams.

FaceSDK offers fast and precise face recognition and identification.

Its consistent recognition rates in any lighting conditions and its ability to be used in conjunction with any webcam make FaceSDK a leader in biometric authentication systems. The SDK works with large and small still images, and offers true real-time support by recognizing and identifying faces in video streams.

This and other performance optimizations lead to dramatically increased performance, allowing surefooted identification and recognition of 66 facial features in real time.

SDK is loaded with features and comes with a host of samples in a variety of programming languages, allowing Web and desktop developers implement advanced face recognition and identification tasks in a matter of minutes.

SDK has been used by the entertainment industry and security specialists, software vendors, and developers of graphic suites to automate a variety of face identification and facial feature recognition tasks, including hands-free authentication and logon systems. Real-time biometric authentication systems can quickly and easily be built around FaceSDK. A variety of photo processing use FaceSDK as their face recognition engine.

What's New

Version 6.5.1: New and improved face recognition engine, offering up to 50 times the matching performance and reaching unprecedented precision.
Face detection speed is 20% higher on Windows.
ARM-based Linux systems are supported.
Speed of enrollment and accuracy in low lighting increased.

Version 6.3.1: Age recognition were added,
More samples were added,
Improved performance of facial feature detection and face recognition.

Version 6.2: New facial features were added,
More samples were added,
Improved performance of face detection and facial feature detection.

Version 6.0: Real-time feature detection on mobile platforms was added,
Facial feature detection speed was increased,
Jitter while tracking facial features in video streams was reduced,
Recognition quality was improved,
IP-cameras are supported for mobiles,
More samples and demo applications were added.

Version 4.0: The speed and accuracy of facial feature detection was improved.
66 facial features detection in real-time was added.
Support for multi-core processor was added.
Support for Java language and CImage class on .NET was added.
More samples and demo applications were added.

Version 3.0: Face recognition improved

Version 2.0: Webcam features added

Version 1.6: Real-time face detection
Detection of multiple faces on a single photo
Runtime size reduced to 1.4 MB